• Fri frakt över 249 kr
  • •
  • Snabba leveranser
  • •
  • Billiga böcker
Kundservice

Du är på sajten för privatpersoner.

Företag, bibliotek eller offentlig verksamhet?

Du handlar på classic.bokus.com, där alla dina funktioner finns intakta.
Till classic.bokus.com
Bokus logotyp. Gå till startsidan.
  • Erbjudanden
  • Nyheter
  • Student
  • Topplistor
  • Barn & ungdom
  • Bokus Play
  • E-böcker
  • Pocketböcker
  • Spel & pussel

10% rabatt på allt med kod: NYSTART10 →

Sidfot

Mina sidor

    Hjälp

    • Kundservice
    • Vanliga frågor och svar
    • Frakt och leverans
    • Retur vid ångerrätt
    • Reklamera vara
    • Betalning
    • Köpvillkor
    • Allmänna villkor
    • Information om webbplatsens tillgänglighet

    Om Bokus

    • Om oss
    • Pressrum
    • För studenter
    • För företag
    • För bibliotek och offentlig verksamhet
    • För leverantörer
    • Hållbarhet

    Populärt

    • Aktuella erbjudanden
    • Presentkort
    • Studentlitteratur
    • Nya böcker
    • Topplistor
    • Signerade böcker
    • Engelska böcker

    Inspiration

    • Boktips
    • BookTok
    • Populära bokserier
    • Barnbokskaraktärer
    • Populära författare
    Logotyp för Bokus
    Följ oss på Facebook (extern länk)Följ oss på Instagram (extern länk)Följ oss på YouTube (extern länk)Följ oss på TikTok (extern länk)
    bokus @ CookiesAnpassa cookiesIntegritetspolicyKöpvillkor
    Till Citymail hemsida (extern länk)Till Budbee hemsida (extern länk)Till Postnord hemsida (extern länk)Till Schenker hemsida (extern länk)Till Early Bird hemsida (extern länk)Till Walleys hemsida (extern länk)
    1. Samhälle och politik
    2. Samhälle och kultur
    3. Kultur och medier
    4. Referensverk och tvärvetenskap

    Computational Approaches to the Network Science of Teams

    AvLiangyue Li,Hanghang Tong

    Inbunden, Engelska, 2020

    641 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Business operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: what communication patterns do high-performing teams have in common? Is it possible to predict a team's performance before it starts work on a project? How can productive team behavior be fostered? This comprehensive review for researchers and practitioners in data mining and social networks surveys recent progress in the emerging field of network science of teams. Focusing on the underlying social network structure, the authors present models and algorithms characterizing, predicting, optimizing, and explaining team performance, along with key applications, open challenges, and future trends.

    Produktinformation

    • Utgivningsdatum:2020-12-03
    • Mått:156 x 234 x 13 mm
    • Vikt:350 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:164
    • Förlag:Cambridge University Press
    • ISBN:9781108498548

    Utforska kategorier

    • Referensverk och tvärvetenskap inom Samhälle och politik
    • Nätverk och kommunikation inom Data och IT
    • Ledarskap och motivation inom Ekonomi och Ledarskap

    Mer om författaren

    Liangyue Li is an applied scientist at Amazon. He received his PhD in computer science from Arizona State University. He has served as a program committee member in top data-mining and artificial intelligence venues (such as SIGKDD, ICML, AAAI and CIKM). He has given a tutorial at WSDM 2018, KDD 2018, and a keynote talk at CIKM 2016 Workshop on Big Network Analytics (BigNet 2016). Hanghang Tong is an associate professor at University of Illinois, Urbana-Champaign since August 2019, Before that, he was an associate professor at Arizona State University, an assistant professor at City College, City University of New York, a research staff member at IBM T.J. Watson Research Center, and a postdoctoral fellow at Carnegie Mellon University, Pennsylvania. He received his M.Sc. and Ph.D. degrees, both in machine learning, from Carnegie Mellon University in 2008 and 2009. His research interest is in large-scale data mining for graphs and multimedia. He received several awards, including NSF CAREER award (2017), ICDM 10-Year Highest Impact Paper Award (2015), four best paper awards (TUP'14, CIKM'12, SDM'08, ICDM'06), six `bests of conference' (ICDM'18, KDD'16, SDM'15, ICDM'15, SDM'11 and ICDM'10), one best demo, honorable mention (SIGMOD'17), and one best demo candidate, second place (CIKM'17). He has published over 100 referred articles. He is the editor-in-chief of SIGKDD Explorations (ACM), an action editor of Data Mining and Knowledge Discovery (Springer), and an associate editor of Neurocomputing Journal (Elsevier); He has served as a program committee member in multiple data-mining, database, and artificial intelligence venues (including SIGKDD, SIGMOD, AAAI, WWW and CIKM).

    Recensioner i media

    'This is a timely book for team science, with a unique perspective that uses computational approaches to study the network effect on team performance. The book has a nice balance of theory, algorithms, and empirical studies. The authors possess years of experience in the field.' Charu Aggarwal, IBM Research AI

    Innehållsförteckning

    • 1. Introduction; 2. Team performance characterization; 3. Team performance prediction; 4. Team performance optimization; 5. Team performance explanation; 6. Human agent teaming; 7. Conclusion and future work.